Search Results (123)

Driverless electric formula racing cars are affected by nonlinear vehicle characteristics, perturbations, and parameter uncertainties during races, which can cause problems such as low accuracy and instability in trajectory tracking. Aiming to address such problems, this paper proposes a control method combining a prescribed performance control with adaptive backstepping fuzzy control (PPC-ABFC) to solve the aforementioned issues and improve the trajectory tracking accuracy and stability of racing cars. This control method is achieved by constructing a combined error model and confining the error within a prescribed performance function. The nonlinear terms, disturbances, and unknown parameters of the model are approximated by a fuzzy logic system (FLS). An adaptive parameter update law is designed to update the learning parameters in real time. The virtual control law and the real control law were designed by using the backstepping method. The stability of the PPC-ABFC closed-loop system was rigorously proved by applying the Lyapunov stability theory. Finally, simulations were conducted to compare the proposed PPC-ABFC method with other algorithms at different speeds. The results demonstrated that the PPC-ABFC method effectively enhances the trajectory tracking performance of driverless electric formula racing cars. Full article

This paper presents the results of real-time experiments conducted to evaluate the performance of a developed adaptive control scheme applied to control the motion of a real closed-kinematic chain mechanism (CKCM) robot manipulator with two degrees of freedom (DOFs). The developed control scheme, referred to as the decentralized adaptive synchronized control scheme (DASCS), was the result of the combination of model reference adaptive control (MRAC) based on the Lyapunov direct method and the synchronization technique. CKCM manipulators were considered in the experimental study due to their advantages over their open-kinematic chain mechanism (OKCM) manipulator counterparts, such as higher stiffness, better stability, and greater payload. The conducted computer simulation study showed that the DASCS was able to asymptotically converge tracking errors to zero, with all the active joints moving synchronously in a prescribed way. One of the important properties of the DASCS is the independence of robot manipulator dynamics, making it computationally efficient and therefore suitable for real-time applications. The present paper reports findings from experiments in which the DASCS was applied to control the above manipulator and carry out various paths. The DASCS’s performance was compared with that of a traditional adaptive control scheme, namely the SMRACS, when both schemes were applied to track the same paths. Full article

In applications where it is crucial that a battery is recharged from the partially discharged state in the minimum time, it is crucial to honor the technological constraints related to maximum safe battery terminal voltage and maximum continuous charging current prescribed by the battery cell manufacturer. To this end, this contribution outlines the design and comprehensive simulation analysis of an adaptive battery charging system relying on battery open-circuit voltage estimation in real time. A pseudo-random binary sequence test signal and model reference adaptive system are used for the estimation of lithium titanate battery cell electrical circuit model parameters, with the design methodology based on the Lyapunov stability criterion. The proposed adaptive charger is assessed against the conventional constant-current/constant-voltage charging system. The effectiveness of the real-time parameter estimator, along with both the adaptive and traditional charging systems for the lithium titanate battery cell, is validated through simulations and experiments on a dedicated battery test bench. Full article

This paper proposes a novel control algorithm for robotic manipulators with unknown nonlinearities and external disturbances. Explicit consideration is given to the physical constraints on joint positions and velocities, ensuring tracking performance without violating prescribed constraints. Finite-time convergence entails significant overshoot magnitudes. A class of nonlinear transformations is employed to ensure state constraint satisfaction while achieving prescribed tracking performance. The command filtered backstepping is employed to circumvent issues of “explosion of terms” in virtual controls. A disturbance observer (DOB), constructed via radial basis function neural networks (RBFNNs), effectively compensates for nonlinearities and time-dependent disturbances. The proposed control law guarantees finite-time stability while preventing position/velocity violations during transients. Simulation results validate the effectiveness of the proposed approach. Full article

Unknown time-varying parameters, along with mismatched and matched disturbances, exist in hydraulic systems, worsening position tracking performance and even destabilizing systems. To address this issue, this article proposes an adaptive full-state prescribed performance position tracking control for hydraulic systems subject both to unknown time-varying parameters and to mismatched and matched disturbances. First, a smooth nonlinear term is skillfully introduced into the controller design so that it can simultaneously cope with both unknown time-varying parameters and disturbances. Next, by integrating the adaptive technique and the prescribed performance function, an adaptive full-state prescribed performance position tracking controller is developed for hydraulic systems in which both the transient and steady performance of all the control errors can be prescribed. A stability analysis then confirms both the prescribed transient performance and the asymptotic steady performance of all the control errors. Finally, the superiority of the proposed controller is also validated by comparison with simulation results. Full article

This paper presents a three-dimensional robust spatiotemporal cooperative guidance law for unmanned aerial vehicles (UAVs) to track a dynamic target under jointly strongly connected topologies, even when some UAVs malfunction. To resolve the infinite gain challenge in existing prescribed-time cooperative guidance laws, a novel bounded-gain prescribed-time stability criterion was formulated. This criterion allows the convergence time of the guidance law to be prescribed arbitrarily without any convergence performance trade-off. Firstly, new prescribed-time disturbance observers are designed to achieve accurate estimations of the target acceleration within a prescribed time regardless of initial conditions. Then, by leveraging a distributed convex hull observer, a tangential acceleration command is proposed to drive arrival times toward a common convex combination within a prescribed time under jointly strongly connected topologies, remaining effective even when partial UAVs fail. Moreover, by utilizing a prescribed-time nonsingular sliding mode control method, normal acceleration commands are developed to guarantee that the line-of-sight angles constraints can be satisfied within a prescribed time. Finally, numerical simulations validate the effectiveness of the proposed guidance law. Full article

To enhance riding comfort for drivers of heavy-duty vehicles, this paper introduces a novel adaptive prescribed performance control (APPC) for active seat suspension systems. The model incorporates dynamic friction and hysteresis damping effects to capture the complex behavior of the seat suspension. The accuracy of the proposed model is validated through experimental data. The controller utilizes a prescribed performance function (PPF) to regulate the dynamic response of the system, combined with an adaptive backstepping control (ABC) method to account for system uncertainties, such as variations in driver weight, friction, suspension stiffness, and damping coefficients. A set of parameter estimators, governed by innovative adaptive laws, compensates for estimation errors. Furthermore, the stability of the controlled system is rigorously demonstrated. Both simulation and experimental tests, including bump and random excitation tests, are conducted to assess the controller performance in both time and frequency domains. The results confirm that the proposed controller effectively mitigates vibrations in the driver–seat system and demonstrates robustness against system uncertainties. Full article

The aim of this study was to investigate the accuracy and stability of both Perception of Velocity (PV) and Perception of Velocity Loss (PVL) over four weeks, without any feedback regarding velocity during training sessions. Fifteen subjects performed six training sessions: four sessions familiarized the athletes with PV and PVL and the final two sessions assessed the accuracy and stability of PV and PVL, with one conducted 48 h after the familiarization and the other after 4 weeks. To assess PV and PVL, two loads (60% 1RM and 80% 1RM) and two velocity losses (20% VL and 40% VL) were employed. PV accuracy was measured by the DeltaScore, the difference between perceived velocity (Vp) and the velocity provided by the encoder (Vr): DetlaScore = Vp − Vr. PVL was measured by the Vscore, the difference between repetitions where the subject perceived the target %VL (Np) and repetitions that actually met it (Nr): Vscore = Np − Nr. The analysis performed revealed no differences in DeltaScore nor in Vscore between the two test sessions performed 4 weeks apart (p > 0.05). On the other hand, the effect of load on both DeltaScore and Vscore was significant in both sessions (p < 0.05). PVL and PV accuracy are stable throughout time. PVL may be used to prescribe and monitor velocity-based training. Conversely, when prescribing training sessions based on PV, it is essential to pair PV with a perception scale and incorporate an encoder when possible. Full article

This study proposes an event-triggered fault-tolerant active disturbance rejection control (ADRC) method for variable-load quadrotors with prescribed performance. The quadrotor, as a nonlinear and underactuated system, faces challenges such as payload variations, actuator faults, and external disturbances, which degrade trajectory tracking accuracy and stability. The proposed approach integrates a cascaded ADRC framework, decoupling the system into position and velocity subsystems, each equipped with extended state observers (ESOs) for real-time disturbance estimation and compensation. To enhance robustness, prescribed performance functions dynamically constrain tracking errors within predefined bounds, while event-triggered mechanisms reduce computational load through condition-based updates of control signals. Additionally, a particle swarm optimization (PSO) algorithm is employed for online parameter tuning, improving adaptability. Theoretical analysis confirms the system stability, and simulation results demonstrate the controller effectiveness in handling actuator faults and variable payloads, ensuring accurate trajectory tracking and reduced resource consumption. The method offers a promising solution for robust and efficient quadrotor control in complex environments. Full article

In time-sensitive aerial missions such as urban surveillance, emergency response, and adversarial airspace operations, achieving rapid and reliable formation control of multi-UAV systems is crucial. This paper addresses the challenge of ensuring robust and efficient formation control under stringent time constraints. The proposed singularity-free prescribed-time formation (PTF) control scheme guarantees task completion within a user-defined time, independent of initial conditions and control parameters. Unlike existing scaling-based prescribed-time methods plagued by unbounded gains and fixed-time strategies with non-tunable convergence bounds, the proposed scheme uses fixed-time stability theory and systematic parameter tuning to avoid singularity issues while ensuring robustness and predictable convergence. The method also accommodates directed communication topologies and unknown external disturbances, allowing follower UAVs to track a dynamic leader and maintain the desired geometric formation. Finally, some simulation results demonstrate the effectiveness of the proposed control strategy, showcasing its superiority over existing methods and validating its potential for practical applications. Full article

Rotator cuff tears are common in individuals over 40, and physical therapy is often prescribed post-surgery. However, access can be limited by cost, convenience, and insurance coverage. CuffLink is a telehealth rehabilitation system that integrates the Strengthening and Stabilization System mechanical exerciser with the interACTION mobile health platform. The system includes a triple-axis accelerometer (LSM6DSOX + LIS3MDL FeatherWing), a rotary encoder, a VL530X time-of-flight sensor, and two wearable BioMech Health IMUs to capture upper-limb motion. CuffLink is designed to facilitate controlled, home-based exercise while enabling clinicians to remotely monitor joint function. Concurrent validity and test–retest reliability were used to assess device accuracy and repeatability. The results showed moderate to good validity for shoulder rotation (ICC = 0.81), device rotation (ICC = 0.94), and linear tracking (from zero: ICC = 0.75 and RMSE = 2.41; from start: ICC = 0.88 and RMSE = 2.02) and good reliability (e.g., RMSEs as low as 1.66 cm), with greater consistency in linear tracking compared to angular measures. Shoulder rotation and abduction exhibited higher variability in both validity and reliability measures. Future improvements will focus on manufacturability, signal stability, and force sensing. CuffLink supports accessible, data-driven rehabilitation and holds promise for advancing digital health in orthopedic recovery. Full article

This paper addresses the challenges of cooperative formation control and prescribed-time tracking for networked quadrotor UAVs under speed and input saturation constraints. A hierarchical control framework including position formation layer and attitude tracking layer is proposed, which achieves full drive control of an underactuated UAV formation system by introducing the expected tracking Euler angle. For the outer-loop position control, a distributed consensus protocol with restricted state and control inputs is designed to ensure formation stability with customizable spacing and bounded velocity. The inner-loop attitude control employs a prescribed-time sliding mode attitude controller (PTSMAC) integrated with a prescribed-time extended state observer (PTESO), enabling rapid convergence within user-defined time and compensating for unmodeled dynamics, wind disturbances, and actuator saturation. The effectiveness of the proposed algorithm was demonstrated through Lyapunov stability. Comparative simulations show that the proposed method has significant advantages in high-precision formation control, convergence time, and input saturation. Full article

Background and Objectives: Low back pain (LBP) is a leading cause of disability worldwide. Core stabilization exercises such as the plank are often prescribed in rehabilitation settlings to improve neuromuscular control and spinal support. However, it remains unclear whether plank performance -accurately reflects trunk function or disability in individuals with LBP. The purpose of this study was to evaluate the relationship between plank endurance and low back pain in adults. Methods: A cross-sectional study was conducted with 117 adults aged 20–61 years (mean 26.0 ± 9.3), including both individuals with and without LBP. Participants completed a plank endurance test and the Modified Oswestry Disability Index (MODI). A subset of fifty-four participants with LBP also completed single-leg bridge tests to assess posterior chain endurance. Statistical analyses included Mann–Whitney U tests to compare plank times by LBP status, logistic regression to evaluate predictors of LBP, and correlation analyses to examine associations between the bridge-to-plank ratio and MODI scores. Results: Contrary to the initial hypothesis, individuals with LBP demonstrated significantly longer plank hold times than those without (U = 1861.00, p = 0.036). Logistic regression indicated that the overall model was statistically significant (χ² = 12.39, p = 0.030), but plank duration was not an independent predictor of LBP (p = 0.070). Among participants with LBP, a higher bridge-to-plank ratio, reflecting relatively greater posterior chain endurance, was significantly associated with lower disability scores (Pearson r = −0.31, p = 0.023; Spearman ρ = −0.32, p = 0.018). Conclusions: These findings suggest that, while plank duration differs by LBP status, longer plank times may not indicate lower risk or severity of back pain. A greater balance of posterior chain to anterior core endurance may be more intricately linked to reduced disability, highlighting the importance of comprehensive core assessment and training strategies in rehabilitation. Full article

This work focuses on fixed-time synchronized trajectory tracking control for unmanned airships subject to time-varying error constraints and unknown disturbances. First, to guarantee strict adherence to prescribed performance bounds, an error transformation function (ETF) is integrated into the control algorithm, which can ensure all tracking errors remain within specified constraints throughout the convergence process. Then, a Norm-Normalized sign (NNS) function is incorporated to develop the control scheme, guaranteeing simultaneous convergence of all tracking error components. Additionally, a novel fixed-time synchronized disturbance observer (FTSDO) is constructed and implemented to achieve precise disturbance estimation while ensuring synchronous convergence of the estimation errors. Finally, the developed control strategy is analytically verified to guarantee fixed-time synchronized stability (FTSS). To assess its performance, multiple simulations are executed. The results clearly demonstrate the proposed control scheme enables the airship to track the prescribed trajectory precisely in fixed time, and the convergence of all tracking error components is achieved synchronously. Full article

Very rarely, the atmosphere produces a natural experiment that, if captured, has the potential to lend insight into the fundamentals of atmospheric behavior. During the North American solar eclipse on 8 April 2024, a prescribed fire on the grounds of Fort Benning produced a smoky haze in Columbus, Georgia, USA. This haze covered the Columbus State University main campus and the nearby Columbus Airport (KCSG) leading up to and during the peak of the eclipse. Automated Surface Observing Station (ASOS) and Georgia Weather Network observations were examined for the event. At the time of temperature minimum, the temperature depression at KCSG was 0.5 °C greater than at nearby ASOS stations. An “eclipse wind” was observed at KCSG but not at the nearby ASOS stations. Based on observations of steady-state air and dewpoint temperatures, together with rapid fluctuations in visibility, we propose the Subcritical Aerosol-Moisture Feedback (SAMF) mechanism, in which subtle feedbacks among particle growth, relative humidity, and scattering of radiation by aerosol-laden air may maintain steady-state thermodynamic conditions. This case study offers a unique opportunity to examine aerosol behavior under transient radiative forcing, suggesting insights into how a smoky environment enhances thermal buffering and stabilizes the boundary-layer response under rare conditions. Full article